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HSI is utilized to measure the quality of solutions.
Parameter tuning has a salient effect on quality of solutions and computational time of evolutionary algorithms.
Usually the quality of solutions is measured by exclusively by the length of the selected route.
The criteria for modifying parameters are the quality of solutions and time spent to find them.
The quality of solutions improves with time, but the process is not uniform.
Amounts of TDS are used to evaluate the quality of solutions.
Also, the quality of solutions ideas was positively correlated with the degree of copying from examples.
The results indicate that ARNA-GA has better search capability and a higher quality of solutions.
Moreover, HCPSO outperforms the compared methods in terms of quality of solutions in short time requirements.
They still have the premature convergence problem resulting in the low quality of solutions.
The experimental results demonstrated the superiority of the proposed algorithm in achieving a high quality of solutions.
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